Presently, in most of large-scale factories and warehouses, counting number of objects such as goods, raw materials and the like, lying at manufacturing units or at distribution units has become a major problem, as manual counting of the objects consumes a lot of time, and is a labor-intensive process which is prone to manual errors. In some instances, it may be required that the objects that are being loaded onto or being unloaded from a carrying vehicle like truck, need to be counted before and/or after transportation. Additionally, for verification and auditing purposes, it may also be required to count the number of objects at both ends of the transportation, i.e., where the objects are being loaded and where the objects are getting unloaded. However, the manual counting process is a very tedious and error-prone task, due to which overall transportation time may be increased.
The existing methods for automatically counting the number of objects placed in a location include analyzing an image of the location/objects and then returning a count of the objects identified in the image. However, the existing methods may return a wrong count of the objects when the objects are present in a cluttered or a distorted background. Further, the existing methods fail to take accurate count of the objects in a location, when the objects are partially visible in the image due to occlusion or incomplete image coverage, or when ends of multiple objects appear to be merged in the image due to shadow or unfavorable lighting conditions. Hence, counting the number of distinct objects accurately in such scenarios may be extremely difficult.
The information disclosed in this background of the disclosure section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.